Product-focused DevOps mustn’t forget the customer

Synopsis

As an organisation becomes product-focused and teams begin to focus their attention on their suite of microservices the organisation must find a way to ensure there is still appropriate focus on the quality of the service being provided to customers.

The power of a product focused approach

I became convinced of the power of a product-focused approach to DevOps when I was working at EA Playfish. Our games teams were product-focused cross-functional and, to an extent, multi-discipline. They were incredibly successful. They had their problems but they were updating their games weekly with a good cadence between content updates and game changes. They reacted to changing situations very quickly and they even pulled together on programme-wide initiatives well. Playfish’s games teams were my inspiration for wanting to scrap the old development, test and ops silos and create teams aligned behind building and supporting products and services.

The insidious risk of having a product-focus

In Next Gen DevOps I examine the implications of taking a product-focused approach to a DevOps transformation. The approach has since been validated by some high profile success stories that I examine in the second edition of the book. Some more recent experiences have led me to conclude that, while the approach is still the right one I, and several others, have missed a trick.

In breaking down a service into microservices or even starting out by considering the bounded contexts of a problem it’s easy to lose sight of the service from the customer perspective.

Background

One of the functions the Ops teams of the past assumed was maintaining a holistic view of the quality and performance of the service as a whole. It’s this trait more than any other that led to friction with development teams. Development teams were often tasked with making changes to specific aspects of a service. Ops would express their concerns about the impact of the proposed changes on performance or availability. The Developers were then caught between an Ops team expressing performance and reliability risks and a Product Manager pushing for the feature changes they need to improve the service. None of the players had the whole picture, very few people in those teams had much experience of expressing non-functional requirements in a functional context and so the result was conflict. While this conflict was counter-productive it ensured there was always someone concerned with the availability and performance of the service-as-a-whole.

Product-focused DevOps is now the way everyone builds their Technology organisations. There are no Operations teams. Engineers are expected to run the services they build. The most successful organisations hire multi-discipline teams so while everyone codes some people are coding tests, some infrastructure and data structures and some are coding business logic. The microservices movement drove this point home as it’s so much easier to deliver smaller, individual services when teams are aligned to those services.

Considering infrastructure configuration, monitoring, build, test execution, deployment and data lifecycle management as products is a logical extension of the microservices or domain-driven development pattern.

However here there be dragons!

When there’s clear ownership of individual microservices who owns the service-as-a-whole? If the answer to that question is everyone then it’s really no-one.

A few years ago the DevOps community got into a discussion about the KPIs that could be used to measure the success of a DevOps transition. As with most such discussions we ended up with some agreement around some common sense measures and a lot of debate about some more esoteric ones.

The ones most people agreed with were:

Mean Time To Recovery.

Time taken to deploy new features measured from merge.

Deployment success (or failure) rate.

Due to the nature of internet debate most of the discussion focussed on what the KPIs should be and very little discussion was had about how the KPIs should be set and managed.

This takes us to the trick I missed when I wrote Next Gen DevOps and the trick many others have missed when they’ve tackled their DevOps transitions.

In our organisations we have a group of people who are already concerned with the whole business and are very focussed on the needs of the customers. These people are used to managing the business with metrics and are comfortable with setting and managing targets. They are the c-level executives. Our COOs are used to managing sales targets and conversation rates, our CFOs are used to managing EBITDA and Net Profit targets. CMOs are used to managing Net Promoter Scores and CTOs are used to managing infrastructure cost targets.

I think we’re making a mistake by not exposing the KPIs and real-time data we have access to so that our executives can actively help us manage risk, productivity and quality of service.

The real power of KPIs

In modern technology organisations we have access to a wealth of data in real-time. We have tools to instantly calculate means and standard deviations from these data points and correlate them to other metrics. We can trend them over time and we can set thresholds and alerts for them.

Every organisation I’ve been in has struggled to manage prioritisation between new feature development and non-functional requirements. The only metric available to most of the executives in those organisations has been availability metrics and page load times if they’re lucky.

Yet it’s fairly logical that if we push new feature development and reduce the time spent on improving the performance of the service service performance will degrade. It’s our job as engineers to identify, record and trend the metrics that expose that degradation. We then need to educate our executives on the meaning of these metrics and give them the levers to manage those metrics accordingly.

Some example KPIs

Let’s get right into the detail to show how executives can help us with even the most complex problems. Technical debt should manifest as a reduction in velocity. If we trend velocity then we can highlight the impact of technical debt as it manifests. If we need to reduce new feature production to resolve technical debt we should be able to demonstrate the impact of that technical debt on velocity and we should be able to see the increase in velocity having resolved the technical debt.

For those organisations still struggling with inflexible infrastructure and software consider the power of Mean time between failure (MTBF). If you’re suffering reliability problems due to under-scale hardware or older software and are struggling to get budget for upgrades MTBF is a powerful metric that can make the point for you.

A common stumbling block for many organisations in the midst of their DevOps transformations is the deployment pipeline. Two words that sum up a wealth of software and configuration complexity. Often building and configuring the deployment pipeline falls to a couple of people who have had some previous experience but no two organisations are quite the same and so there are always some new stumbling blocks. If you trend the Time taken to deploy new features measured from merge. You can easily make the point for getting some help from other people around the organisation to help build a better deployment pipeline.

The trick with all of this is to measure these metrics before you need them so you can demonstrate how they change with investment, prioritisation and other changes.

Implementation

Get your technical leadership team to meet with the executive team, discuss the KPIs that matter to you and some that don’t matter yet that might. Educate everyone in the room about the way the KPIs are measured so the metrics have context and people can have confidence in them. Create a process for managing the KPIs and then start measuring them, in real-time and display them on dashboards. Set up sessions to discuss the inevitable blips and build a partnership to manage the business using the metrics that really matter.